Genome-Wide Co-Expression Distributions as a Metric to Prioritize Genes of Functional Importance.

Genome-wide gene expression analysis are routinely used to gain a systems-level understanding of complex processes, including network connectivity. Network connectivity tends to be built on a small subset of extremely high co-expression signals that are deemed significant, but this overlooks the vast majority of pairwise signals. Here, we developed a computational pipeline to assign to every gene its pair-wise genome-wide co-expression distribution to one of 8 template distributions shapes varying between unimodal, bimodal, skewed, or symmetrical, representing different proportions of positive and negative correlations. We then used a hypergeometric test to determine if specific genes (regulators versus non-regulators) and properties (differentially expressed or not) are associated with a particular distribution shape. We applied our methodology to five publicly available RNA sequencing (RNA-seq) datasets from four organisms in different physiological conditions and tissues. Our results suggest that genes can be assigned consistently to pre-defined distribution shapes, regarding the enrichment of differential expression and regulatory genes, in situations involving contrasting phenotypes, time-series, or physiological baseline data. There is indeed a striking additional biological signal present in the genome-wide distribution of co-expression values which would be overlooked by currently adopted approaches. Our method can be applied to extract further information from transcriptomic data and help uncover the molecular mechanisms involved in the regulation of complex biological process and phenotypes.

In silico validation of pooled genotyping strategies for genomic evaluation in Angus cattle.

In this study, we aimed to assess the value of genotyping DNA pools as a strategy to generate accurate and cost-effective genomic estimated breeding values (GEBV) of sires in multi-sire mating systems. In order to do that, we used phenotypic records of 2,436 Australian Angus cattle from 174 sires, including yearling weight (YWT; N = 1,589 records), coat score (COAT; N = 2,026 records), and Meat Standards Australia marbling score (MARB; N = 1,304 records). Phenotypes were adjusted for fixed effects and age at measurement and pools of 2, 5, 10, 15, 20, and 25 animals were explored. Pools were created either by phenotype or at random. When pools were created at random, 10 replicates were examined to provide a measure of sampling variation. The relative accuracy of each pooling strategy was measured by the Pearson correlation coefficient between the sire's GEBV with pooled progeny and the GEBV using individually genotyped progeny. Random pools allow the computation of sire GEBV that are, on average, moderately correlated (i.e., r > 0.5 at pool sizes [PS] ≤ 10) with those obtained without pooling. However, for pools assigned at random, the difference between the best and the worst relative accuracy obtained out of the 10 replicates was as high as 0.41 for YWT, 0.36 for COAT, and 0.61 for MARB. This uncertainty associated with the relative accuracy of GEBV makes randomly assigning animals to pools an unreliable approach. In contrast, pooling by phenotype allowed the estimation of sires' GEBV with a relative accuracy ≥ 0.9 at PS < 10 for all three phenotypes. Moreover, even with larger PS, the lowest relative accuracy obtained was 0.88 (YWT, PS = 20). In agreement with results using simulated data, we conclude that pooling by phenotype is a robust approach to implementing genomic evaluation using commercial herd data, and PS larger than 10 individuals can be considered.

Pooled genotyping strategies for the rapid construction of genomic reference populations1.

The growing concern with the environment is making important for livestock producers to focus on selection for efficiency-related traits, which is a challenge for commercial cattle herds due to the lack of pedigree information. To explore a cost-effective opportunity for genomic evaluations of commercial herds, this study compared the accuracy of bulls' genomic estimated breeding values (GEBV) using different pooled genotype strategies. We used ten replicates of previously simulated genomic and phenotypic data for one low (t1) and one moderate (t2) heritability trait of 200 sires and 2,200 progeny. Sire's GEBV were calculated using a univariate mixed model, with a hybrid genomic relationship matrix (h-GRM) relating sires to: 1) 1,100 pools of 2 animals; 2) 440 pools of 5 animals; 3) 220 pools of 10 animals; 4) 110 pools of 20 animals; 5) 88 pools of 25 animals; 6) 44 pools of 50 animals; and 7) 22 pools of 100 animals. Pooling criteria were: at random, grouped sorting by t1, grouped sorting by t2, and grouped sorting by a combination of t1 and t2. The same criteria were used to select 110, 220, 440, and 1,100 individual genotypes for GEBV calculation to compare GEBV accuracy using the same number of individual genotypes and pools. Although the best accuracy was achieved for a given trait when pools were grouped based on that same trait (t1: 0.50-0.56, t2: 0.66-0.77), pooling by one trait impacted negatively on the accuracy of GEBV for the other trait (t1: 0.25-0.46, t2: 0.29-0.71). Therefore, the combined measure may be a feasible alternative to use the same pools to calculate GEBVs for both traits (t1: 0.45-0.57, t2: 0.62-0.76). Pools of 10 individuals were identified as representing a good compromise between loss of accuracy (~10%-15%) and cost savings (~90%) from genotype assays. In addition, we demonstrated that in more than 90% of the simulations, pools present higher sires' GEBV accuracy than individual genotypes when the number of genotype assays is limited (i.e., 110 or 220) and animals are assigned to pools based on phenotype. Pools assigned at random presented the poorest results (t1: 0.07-0.45, t2: 0.14-0.70). In conclusion, pooling by phenotype is the best approach to implementing genomic evaluation using commercial herd data, particularly when pools of 10 individuals are evaluated. While combining phenotypes seems a promising strategy to allow more flexibility to the estimates made using pools, more studies are necessary in this regard.

Evaluation of nonadditive effects in yearling weight of tropical beef cattle.

Nonadditive effects may contribute to genetic variation of complex traits. Their inclusion in genetic evaluation models may therefore improve breeding value estimates and lead to more accurate selection decisions. In this study, we evaluated a systematic series of models accounting for additive, dominance and first-order epistatic interaction (additive by additive, GxG; additive by dominance, GxD; and dominance by dominance, DxD) on body yearling weight (YWT) of 2,550 Tropical Composite (TC) and 2,111 Brahman (BB) cattle in Australia. For both breeds, similar estimates of additive and phenotypic variances and narrow and broad-sense heritability values were obtained across the evaluated models except when GxG effect was considered. In this case, additive variance was slightly lower than that obtained in the models which do not consider this effect. The estimated dominance and epistatic variances from additive and dominance effects (AD) and additive, dominance and epistatic effects models (ADE) were greater than that ADH and ADEH models (as described above plus heterozygosity as a covariate). However, all genetic parameter estimates were associated with a large standard deviation. Averaged across ADH and ADHE models, the magnitude of dominance variance compared to the phenotypic variance of YWT was 14% (BB) and 10% (TC). The magnitude of epistasis compared to the phenotypic variance for BB and TC was 17% and 29%, respectively for GxG; 0.7% and 0% for GxD; and 0% and 0% for DxD. The inclusion of nonadditive effects slightly improves the predictive accuracy of breeding values from 0.28 for A to 0.33 for ADHEGxG and from 0.18 for A to 0.23 ADEGxD in BB and TC cattle. Models that included heterozygosity (ADH and ADHE) must be used to estimate nonadditive genetic variance components. A 1 Mb sliding window analysis identified a region on BTA 14 explaining 10.08% and 1.21% of total genetic variance (additive + dominance) of YWT in BB and TC, respectively. Our results suggest that dominance, epistasis, and heterozygosity should be included in models for genetic parameters estimation. To identify the animals with the highest additive genetic value in selection decisions, only the additive effect should be used in evaluation models.

STAT6, PBX2, and PBRM1 Emerge as Predicted Regulators of 452 Differentially Expressed Genes Associated With Puberty in Brahman Heifers.

The liver plays a central role in metabolism and produces important hormones. Hepatic estrogen receptors and the release of insulin-like growth factor 1 (IGF1) are critical links between liver function and the reproductive system. However, the role of liver in pubertal development is not fully understood. To explore this question, we applied transcriptomic analyses to liver samples of pre- and post-pubertal Brahman heifers and identified differentially expressed (DE) genes and genes encoding transcription factors (TFs). Differential expression of genes suggests potential biological mechanisms and pathways linking liver function to puberty. The analyses identified 452 DE genes and 82 TF with significant contribution to differential gene expression by using a regulatory impact factor metric. Brain-derived neurotrophic factor was observed as the most down-regulated gene (P = 0.003) in post-pubertal heifers and we propose this gene influences pubertal development in Brahman heifers. Additionally, co-expression network analysis provided evidence for three TF as key regulators of liver function during pubertal development: the signal transducer and activator of transcription 6, PBX homeobox 2, and polybromo 1. Pathway enrichment analysis identified transforming growth factor-beta and Wnt signaling pathways as significant annotation terms for the list of DE genes and TF in the co-expression network. Molecular information regarding genes and pathways described in this work are important to further our understanding of puberty onset in Brahman heifers.

Neuropeptidome of the Hypothalamus and Pituitary Gland of Indicine × Taurine Heifers: Evidence of Differential Neuropeptide Processing in the Pituitary Gland before and after Puberty.

Puberty in cattle is regulated by an endocrine axis, which includes a complex milieu of neuropeptides in the hypothalamus and pituitary gland. The neuropeptidome of hypothalamic-pituitary gland tissue of pre- (PRE) and postpubertal (POST) Bos indicus-influenced heifers was characterized, followed by quantitative analysis of 51 fertility-related neuropeptides in these tissues. Comparison of peptide abundances with gene expression levels allowed assessment of post-transcriptional peptide processing. On the basis of classical cleavage, 124 mature neuropeptides from 35 precursor proteins were detected in hypothalamus and pituitary gland tissues of three PRE and three POST Brangus heifers. An additional 19 peptides (cerebellins, PEN peptides) previously reported as neuropeptides that did not follow classical cleavage were also identified. In the pre-pubertal hypothalamus, a greater diversity of neuropeptides (25.8%) was identified relative to post-pubertal heifers, while in the pituitary gland, 38.6% more neuropeptides were detected in the post-pubertal heifers. Neuro-tissues of PRE and POST heifers revealed abundance differences ( p < 0.05) in peptides from protein precursors involved in packaging and processing (e.g., the granin family and ProSAAS) or neuron stimulation (PENK, CART, POMC, cerebellins). On their own, the transcriptome data of the precursor genes could not predict the neuropeptide profile in the exact same tissues in several cases. This provides further evidence of the importance of differential processing of the neuropeptide precursors in the pituitary before and after puberty.

Weighting genomic and genealogical information for genetic parameter estimation and breeding value prediction in tropical beef cattle.

A combined matrix that exploits genealogy together with marker-based information could improve the selection of elite individuals in breeding programs. We present genetic parameters for adaptive and growth traits in beef cattle by exploring linear combinations of pedigree-based (A) and marker-based (G) relationship matrices. We use a data set with 2,111 Brahman (BB) and 2,550 Tropical Composite (TC) cattle with genotypes for 729,068 SNP, and phenotypes for five traits. A weighted relationship matrix (WRM) combining G and A was constructed as WRM = λG + (1 - λ)A. The weight (λ) was explored at values from 0.0 to 1.0, at 0.1 intervals. Additionally, four alternative G matrices, in the WRM, were evaluated according to the selection of SNP used to generate them: 1) Gw: all autosomal SNP with minor allele frequency (MAF) > 1%; 2) Gg: autosomal SNP with MAF > 1% and mapped inside to gene coding regions; 3) Gp: autosomal SNP with MAF > 1% and previously reported to have significant pleiotropic effect in these two populations; and 4) Gc: autosomal SNP with MAF > 1% and with significant correlated effects previously reported in both BB and TC populations. In addition, two A matrices were evaluated: 1) A: all relationships between animals were considered after tracing back known ancestors; and 2) Ad: a distorted A matrix where a random 1% of the off-diagonal nonzero values were set to zero to simulate relationship errors. Five independent Ad matrices were explored each with a different random 1% of relationships masked. Criteria for comparing the resulting WRM included estimates of heritability (h2) and cross-validation accuracy (ACC) of genomic estimated breeding values. The choice of WRM had a greater impact on h2 than on ACC estimates. The 1% errors introduced in pedigree relationships generated large distortion in genetic parameters and ACC estimates. However, employing a λ > 0.7 was an efficient mechanism to compensate for the errors in A. Additionally, although significant (P-value < 0.0001), we found no consistent relationship between the type of SNP used to compute G and h2 or ACC estimates. We devised the optimal value of λ for maximum h2 and ACC at λ = 0.7 suggesting a 70% and 30% weighting to genomic and genealogical information, respectively, as an optimal strategy to compensate for pedigree errors, to improve genetic parameters estimates and lead to more accurate selection decisions.

The Bos taurus-Bos indicus balance in fertility and milk related genes.

Numerical approaches to high-density single nucleotide polymorphism (SNP) data are often employed independently to address individual questions. We linked independent approaches in a bioinformatics pipeline for further insight. The pipeline driven by heterozygosity and Hardy-Weinberg equilibrium (HWE) analyses was applied to characterize Bos taurus and Bos indicus ancestry. We infer a gene co-heterozygosity network that regulates bovine fertility, from data on 18,363 cattle with genotypes for 729,068 SNP. Hierarchical clustering separated populations according to Bos taurus and Bos indicus ancestry. The weights of the first principal component were subjected to Normal mixture modelling allowing the estimation of a gene's contribution to the Bos taurus-Bos indicus axis. We used deviation from HWE, contribution to Bos indicus content and association to fertility traits to select 1,284 genes. With this set, we developed a co-heterozygosity network where the group of genes annotated as fertility-related had significantly higher Bos indicus content compared to other functional classes of genes, while the group of genes associated with milk production had significantly higher Bos taurus content. The network analysis resulted in capturing novel gene associations of relevance to bovine domestication events. We report transcription factors that are likely to regulate genes associated with cattle domestication and tropical adaptation. Our pipeline can be generalized to any scenarios where population structure requires scrutiny at the molecular level, particularly in the presence of a priori set of genes known to impact a phenotype of evolutionary interest such as fertility.

Estimating the genetic merit of sires by using pooled DNA from progeny of undetermined pedigree.

BACKGROUND: DNA-based predictions for hard-to-measure production traits hold great promise for selective breeding programs. DNA pooling might provide a cheap genomic approach to use phenotype data from commercial flocks which are commonly group-mated with parentage unknown. This study on sheep explores if genomic breeding values for stud sires can be estimated from genomic relationships that were obtained from pooled DNA in combination with phenotypes from commercial progeny. METHODS: Phenotypes used in this study were categorical data. Blood was pooled strategically aiming at even pool sizes and within sex and phenotype category. A hybrid genomic relationship matrix was constructed relating pools to sires. This matrix was used to determine the contribution of sires to each of the pools and therefore phenotype category by using a simple regression approach. Genomic breeding values were also estimated using the hybrid genomic relationship matrix. RESULTS: We demonstrated that, using pooled DNA, the genetic performance of sires can be illustrated as their contribution to phenotype categories and can be expressed as a regression coefficient. Genomic estimated breeding values for sires were equivalent to the regression coefficients and are a commonly used industry tool. CONCLUSIONS: Genotyping of DNA from pooled biological samples offers a cheap method to link phenotypic information from commercial production animals to the breeding population and can be turned into information on the genetic value of stud sires for traits that cannot be measured in the stud environment.

Candidate Gene Expression in Bos indicus Ovarian Tissues: Prepubertal and Postpubertal Heifers in Diestrus.

Growth factors such as bone morphogenetic proteins 6, 7, 15, and two isoforms of transforming growth factor-beta (BMP6, BMP7, BMP15, TGFB1, and TGFB2), and insulin-like growth factor system act as local regulators of ovarian follicular development. To elucidate if these factors as well as others candidate genes, such as estrogen receptor 1 (ESR1), growth differentiation factor 9 (GDF9), follicle-stimulating hormone receptor (FSHR), luteinizing hormone receptor (LHR), bone morphogenetic protein receptor, type 2 (BMPR2), type 1 insulin-like growth factor receptor (IGFR1), and key steroidogenic enzymes cytochrome P450 aromatase and 3-ß-hydroxysteroid dehydrogenase (CYP19A1 and HSD3B1) could modulate or influence diestrus on the onset of puberty in Brahman heifers, their ovarian mRNA expression was measured before and after puberty (luteal phase). Six postpubertal (POST) heifers were euthanized on the luteal phase of their second cycle, confirmed by corpus luteum observation, and six prepubertal (PRE) heifers were euthanized in the same day. Quantitative real-time PCR analysis showed that the expression of FSHR, BMP7, CYP19A1, IGF1, and IGFR1 mRNA was greater in PRE heifers, when contrasted to POST heifers. The expression of LHR and HSD3B1 was lower in PRE heifers. Differential expression of ovarian genes could be associated with changes in follicular dynamics and different cell populations that have emerged as consequence of puberty and the luteal phase. The emerging hypothesis is that BMP7 and IGF1 are co-expressed and may modulate the expression of FSHR, LHR and IGFR1, and CYP19A1. BMP7 could influence the downregulation of LHR and upregulation of FSHR and CYP19A1, which mediates the follicular dynamics in heifer ovaries. Upregulation of IGF1 expression prepuberty, compared to postpuberty diestrus, correlates with increased levels FSHR and CYP19A1. Thus, BMP7 and IGF1 may play synergic roles and were predicted to interact, from the expression data (P = 0.07, r = 0.84). The role of these co-expressed genes in puberty and heifers luteal phase merits further research.

Polymorphisms and genes associated with puberty in heifers.

Puberty onset is a multifactorial process influenced by genetic determinants and environmental conditions, especially nutritional status. Genes, genetic variations, and regulatory networks compose the molecular basis of achieving puberty. In this article, we reviewed the discovery of multiple polymorphisms and genes associated with heifer puberty phenotypes and discuss the opportunities to use this evolving knowledge of genetic determinants for breeding early pubertal Bos indicus-influenced cattle. The discovery of polymorphisms and genes was mainly achieved through candidate gene studies, quantitative trait loci analyses, genome-wide association studies, and recently, global gene expression studies (transcriptome). These studies are recapitulated and summarized in the current review.

Genomic correlation: harnessing the benefit of combining two unrelated populations for genomic selection.

BACKGROUND: The success of genomic selection in animal breeding hinges on the availability of a large reference population on which genomic-based predictions of additive genetic or breeding values are built. Here, we explore the benefit of combining two unrelated populations into a single reference population. METHODS: The datasets consisted of 1829 Brahman and 1973 Tropical Composite cattle with measurements on five phenotypes relevant to tropical adaptation and genotypes for 71,726 genome-wide single nucleotide polymorphisms (SNPs). The underlying genomic correlation for the same phenotype across the two breeds was explored on the basis of consistent linkage disequilibrium (LD) phase and marker effects in both breeds. RESULTS: The proportion of genetic variance explained by the entire set of SNPs ranged from 37.5 to 57.6 %. Estimated genomic correlations were drastically affected by the process used to select SNPs and went from near 0 to more than 0.80 for most traits when using the set of SNPs with significant effects and the same LD phase in the two breeds. We found that, by carefully selecting the subset of SNPs, the missing heritability can be largely recovered and accuracies in genomic predictions can be improved six-fold. However, the increases in accuracy might come at the expense of large biases. CONCLUSIONS: Our results offer hope for the effective implementation of genomic selection schemes in situations where the number of breeds is large, the sample size within any single breed is small and the breeding objective includes many phenotypes.

The histone variant H2A.Z is dynamically expressed in the developing mouse placenta and in differentiating trophoblast stem cells.

The histone variant H2A.Z is important in establishing new chromatin environments necessary for permitting changes in gene expression and thus differentiation in mouse embryonic stem (mES) cells. In this study we show that H2A.Z is highly expressed in the early mouse placenta, and is specifically limited to progenitor-like trophoblast cells. Using in vitro models, we revealed distinct differences in H2A.Z abundance between undifferentiated, differentiating and differentiated mouse trophoblast stem (mTS) cells. Our work supports the hypothesis that in addition to roles in differentiating mES cells, H2A.Z is also involved in the differentiation of extra-embryonic tissues.

Non-synonymous mutations mapped to chromosome X associated with andrological and growth traits in beef cattle.

BACKGROUND: Previous genome-wide association analyses identified QTL regions in the X chromosome for percentage of normal sperm and scrotal circumference in Brahman and Tropical Composite cattle. These traits are important to be studied because they are indicators of male fertility and are correlated with female sexual precocity and reproductive longevity. The aim was to investigate candidate genes in these regions and to identify putative causative mutations that influence these traits. In addition, we tested the identified mutations for female fertility and growth traits. RESULTS: Using a combination of bioinformatics and molecular assay technology, twelve non-synonymous SNPs in eleven genes were genotyped in a cattle population. Three and nine SNPs explained more than 1% of the additive genetic variance for percentage of normal sperm and scrotal circumference, respectively. The SNPs that had a major influence in percentage of normal sperm were mapped to LOC100138021 and TAF7L genes; and in TEX11 and AR genes for scrotal circumference. One SNP in TEX11 was explained ~13% of the additive genetic variance for scrotal circumference at 12 months. The tested SNP were also associated with weight measurements, but not with female fertility traits. CONCLUSIONS: The strong association of SNPs located in X chromosome genes with male fertility traits validates the QTL. The implicated genes became good candidates to be used for genetic evaluation, without detrimentally influencing female fertility traits.

Low frequency of Y anomaly detected in Australian Brahman cow-herds.

Indicine cattle have lower reproductive performance in comparison to taurine. A chromosomal anomaly characterized by the presence Y markers in females was reported and associated with infertility in cattle. The aim of this study was to investigate the occurrence of the anomaly in Brahman cows. Brahman cows (n = 929) were genotyped for a Y chromosome specific region using real time-PCR. Only six out of 929 cows had the anomaly (0.6%). The anomaly frequency was much lower in Brahman cows than in the crossbred population, in which it was first detected. It also seems that the anomaly doesn't affect pregnancy in the population. Due to the low frequency, association analyses couldn't be executed. Further, SNP signal of the pseudoautosomal boundary region of the Y chromosome was investigated using HD SNP chip. Pooled DNA of "non-pregnant" and "pregnant" cows were compared and no difference in SNP allele frequency was observed. Results suggest that the anomaly had a very low frequency in this Australian Brahman population and had no effect on reproduction. Further studies comparing pregnant cows and cows that failed to conceive should be executed after better assembly and annotation of the Y chromosome in cattle.

The genetic architecture of climatic adaptation of tropical cattle.

Adaptation of global food systems to climate change is essential to feed the world. Tropical cattle production, a mainstay of profitability for farmers in the developing world, is dominated by heat, lack of water, poor quality feedstuffs, parasites, and tropical diseases. In these systems European cattle suffer significant stock loss, and the cross breeding of taurine x indicine cattle is unpredictable due to the dilution of adaptation to heat and tropical diseases. We explored the genetic architecture of ten traits of tropical cattle production using genome wide association studies of 4,662 animals varying from 0% to 100% indicine. We show that nine of the ten have genetic architectures that include genes of major effect, and in one case, a single location that accounted for more than 71% of the genetic variation. One genetic region in particular had effects on parasite resistance, yearling weight, body condition score, coat colour and penile sheath score. This region, extending 20 Mb on BTA5, appeared to be under genetic selection possibly through maintenance of haplotypes by breeders. We found that the amount of genetic variation and the genetic correlations between traits did not depend upon the degree of indicine content in the animals. Climate change is expected to expand some conditions of the tropics to more temperate environments, which may impact negatively on global livestock health and production. Our results point to several important genes that have large effects on adaptation that could be introduced into more temperate cattle without detrimental effects on productivity.

Variation in genes involved in epigenetic processes offers insights into tropically adapted cattle diversity.

We evaluated the relevance of the BovineHD Illumina SNP chip with respect to genes involved in epigenetic processes. Genotypes for 729,068 SNP on two tropical cattle breeds of Australia were used: Brahman (n = 2112) and Tropical Composite (n = 2550). We used data mining approaches to compile a list of bovine protein-coding genes involved in epigenetic processes. These genes represent 9 functional categories that contain between one (histone demethylases) and 99 (chromatin remodeling factors) genes. A total of 3091 SNP mapped to positions within 3000 bp of the 193 coding regions of those genes, including 113 SNP in transcribed regions, 2738 in intronic regions and 240 in up- or down-stream regions. For all these SNP categories, we observed differences in the allelic frequencies between Brahman and Tropical Composite cattle. These differences were larger than those observed for the entire set of 729,068 SNP (P = 1.79 x 10(-5)). A multidimensional scaling analysis using only the 113 SNP in transcribed regions allowed for the separation of the two populations and this separation was comparable to the one obtained with a random set of 113 SNP (Principal Component 1 r (2) > 0.84). To further characterize the differences between the breeds we defined a gene-differentiation metric based on the average genotypic frequencies of SNP connected to each gene and compared both cattle populations. The 10% most differentiated genes were distributed across 10 chromosomes, with significant (P < 0.05) enrichment on BTA 3 and 10. The 10% most conserved genes were located in 12 chromosomes. We conclude that there is variation between cattle populations in genes connected to epigenetic processes, and this variation can be used to differentiate cattle breeds. More research is needed to fully characterize the use of these SNP and its potential as means to further our understanding of biological variation and epigenetic processes.

Evidence for positive selection of taurine genes within a QTL region on chromosome X associated with testicular size in Australian Brahman cattle.

BACKGROUND: Previous genome-wide association studies have identified significant regions of the X chromosome associated with reproductive traits in two Bos indicus-influenced breeds: Brahman cattle and Tropical Composites. Two QTL regions on this chromosome were identified in both breeds as strongly associated with scrotal circumference measurements, a reproductive trait previously shown to be useful for selection of young bulls. Scrotal circumference is genetically correlated with early age at puberty in both male and female offspring. These QTL were located at positions 69-77 and 81-92 Mb respectively, large areas each to which a significant number of potential candidate genes were mapped. RESULTS: To further characterise these regions, a bioinformatic approach was undertaken to identify novel non-synonymous SNP within the QTL regions of interest in Brahman cattle. After SNP discovery, we used conventional molecular assay technologies to perform studies of two candidate genes in both breeds. Non-synonymous SNP mapped to Testis-expressed gene 11 (Tex11) were associated (P < 0.001) with scrotal circumference in both breeds, and associations with percentage of normal sperm cells were also observed (P < 0.05). Evidence for recent selection was found as Tex11 SNP form a haplotype segment of Bos taurus origin that is retained within Brahman and Tropical Composite cattle with greatest reproductive potential. CONCLUSIONS: Association of non-synonymous SNP presented here are a first step to functional genetic studies. Bovine species may serve as a model for studying the role of Tex11 in male fertility, warranting further in-depth molecular characterisation.

Depletion of testis cell populations in pre-pubertal Bos indicus cattle by irradiation.

Recovery of spermatogenesis following a single dose of irradiation was evaluated in pre-pubertal Brahman bulls, after receiving a single dose of 3, 6, 9 or 12Gray (Gy) irradiation. Biopsy samples of testis tissue were collected and processed for immunohistology at various times following irradiation. Spermatogenic recovery was defined by the changes in tubule diameter, and absolute numbers of undifferentiated spermatogonia (PLZF positive cells) and Sertoli cells (GATA-4 positive cells) per tubule cross section. The effect of irradiation on the depletion of testicular cells was dose-dependent. Immunohistological results from both the 9 and 12Gy group showed degeneration of seminiferous tubules, compared with other doses and controls. From 2 weeks after the treatment, irradiation resulted in a significant and dramatic reduction in tubule diameter (up to 40%), number of undifferentiated spermatogonia (up to 90%) and Sertoli cells (up to 70%), which was sustained for up to 16 weeks post-irradiation in 9 and 12Gy groups (P<0.0001). However, a moderate depletion effect was observed in the 6Gy treatment groups, compared with 9 and 12Gy doses. The 6Gy treatment had significant effects on spermatogonia (up to 79% reduction) and Sertoli cell (30% reduction) numbers following irradiation (P<0.0001). In contrast, the 3Gy dose had no significant effect at either 3 or 5 weeks post-irradiation on tubule diameter, spermatogonia or Sertoli cells. In conclusion, the results from the current study suggest that treatment of recipient testes with a single dose of 6Gy irradiation can temporarily deplete spermatogonial cells in pre-pubertal Brahman bulls, whilst minimising the impact on Sertoli cells and tubule morphology.

Genomic regions associated with fertility traits in male and female cattle: advances from microsatellites to high-density chips and beyond.

A current challenge in genetic improvement of cattle is to identify genomic selection strategies that could work across breeds. Breed differences, scarcity of data, and lack of quantitative trait loci (QTL) validation contribute to this challenge. We conducted a review of the literature to identify QTL, markers, and candidate genes that are associated with fertility across breeds to arrive at an integrated view of bovine fertility genomics and to guide the direction of future studies. This review considers both male and female fertility traits as these are economically relevant for all breeds and production systems. Regions associated with fertility traits were found in each of the 30 bovine chromosomes, confirming the complexity of these polygenic traits. Across breeds, regions on chromosomes 1, 5, 14, and 16 were associated with female reproductive traits. The X chromosome was associated with male reproductive traits in both dairy and beef bulls. It has recently been proposed that a Y chromosome anomaly may be involved in infertility in cows. Knowledge of these QTL may assist discovery of causative mutations and has the potential to improve the accuracy of genomic selection, especially across breeds of cattle.